path: "tensorflow.optimizers.AdamW"
tf_class {
  is_instance: "<class \'keras.optimizers.adamw.AdamW\'>"
  is_instance: "<class \'keras.optimizers.optimizer.Optimizer\'>"
  is_instance: "<class \'keras.optimizers.optimizer._BaseOptimizer\'>"
  is_instance: "<class \'tensorflow.python.trackable.autotrackable.AutoTrackable\'>"
  is_instance: "<class \'tensorflow.python.trackable.base.Trackable\'>"
  is_instance: "<type \'object\'>"
  member {
    name: "iterations"
    mtype: "<type \'property\'>"
  }
  member {
    name: "learning_rate"
    mtype: "<type \'property\'>"
  }
  member {
    name: "lr"
    mtype: "<type \'property\'>"
  }
  member {
    name: "variables"
    mtype: "<type \'property\'>"
  }
  member_method {
    name: "__init__"
    argspec: "args=[\'self\', \'learning_rate\', \'weight_decay\', \'beta_1\', \'beta_2\', \'epsilon\', \'amsgrad\', \'clipnorm\', \'clipvalue\', \'global_clipnorm\', \'use_ema\', \'ema_momentum\', \'ema_overwrite_frequency\', \'jit_compile\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.004\', \'0.9\', \'0.999\', \'1e-07\', \'False\', \'None\', \'None\', \'None\', \'False\', \'0.99\', \'None\', \'True\', \'AdamW\'], "
  }
  member_method {
    name: "add_variable"
    argspec: "args=[\'self\', \'shape\', \'dtype\', \'initializer\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\'], "
  }
  member_method {
    name: "add_variable_from_reference"
    argspec: "args=[\'self\', \'model_variable\', \'variable_name\', \'shape\', \'initial_value\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
  }
  member_method {
    name: "aggregate_gradients"
    argspec: "args=[\'self\', \'grads_and_vars\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "apply_gradients"
    argspec: "args=[\'self\', \'grads_and_vars\', \'name\', \'skip_gradients_aggregation\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'False\'], "
  }
  member_method {
    name: "build"
    argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "compute_gradients"
    argspec: "args=[\'self\', \'loss\', \'var_list\', \'tape\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "exclude_from_weight_decay"
    argspec: "args=[\'self\', \'var_list\', \'var_names\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
  }
  member_method {
    name: "finalize_variable_values"
    argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "from_config"
    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "get_config"
    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "load_own_variables"
    argspec: "args=[\'self\', \'store\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "minimize"
    argspec: "args=[\'self\', \'loss\', \'var_list\', \'tape\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "save_own_variables"
    argspec: "args=[\'self\', \'store\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "set_weights"
    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "update_step"
    argspec: "args=[\'self\', \'gradient\', \'variable\'], varargs=None, keywords=None, defaults=None"
  }
}
